An issue of concern: unique truncated ORF8 protein variants of SARS-CoV-2

Open reading frame 8 (ORF8) shows one of the highest levels of variability among accessory proteins in Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the causative agent of Coronavirus Disease 2019 (COVID-19). It was previously reported that the ORF8 protein inhibits the presentation of viral antigens by the major histocompatibility complex class I (MHC-I), which interacts with host factors involved in pulmonary inflammation. The ORF8 protein assists SARS-CoV-2 in evading immunity and plays a role in SARS-CoV-2 replication. Among many contributing mutations, Q27STOP, a mutation in the ORF8 protein, defines the B.1.1.7 lineage of SARS-CoV-2, engendering the second wave of COVID-19. In the present study, 47 unique truncated ORF8 proteins (T-ORF8) with the Q27STOP mutations were identified among 49,055 available B.1.1.7 SARS-CoV-2 sequences. The results show that only one of the 47 T-ORF8 variants spread to over 57 geo-locations in North America, and other continents, which include Africa, Asia, Europe and South America. Based on various quantitative features, such as amino acid homology, polar/non-polar sequence homology, Shannon entropy conservation, and other physicochemical properties of all specific 47 T-ORF8 protein variants, nine possible T-ORF8 unique variants were defined. The question as to whether T-ORF8 variants function similarly to the wild type ORF8 is yet to be investigated. A positive response to the question could exacerbate future COVID-19 waves, necessitating severe containment measures.


INTRODUCTION
The world is proceeding through a very difficult time due to the Coronavirus Disease 2019 , of which the causative agent is the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) (Hu et al., 2021;Yuen et al., 2020;Matheson & Lehner, 2020;Wu et al., 2020;Fontanet et al., 2021). There are nine open reading frames (ORFs), which encode accessory proteins important for the modulation of metabolism in infected host cells and innate immunity evasion via a complicated signalome and an interactome (Ren et al., 2020;Hassan et al., 2021cHassan et al., , 2020bDíaz, 2020;Stukalov et al., 2021). The ORF8 protein is one of the most rapidly evolving accessory proteins among the beta coronaviruses, not only due to its ability to interfere with host immune response, but also with regards to its several missense mutations detected to date (Li et al., 2020;Zinzula, 2021;Hassan et al., 2021a;Flower et al., 2021). ORF8 directly interacts with major histocompatibility complex class I (MHC-I) both in vitro and in vivo, and is downregulated, which impairs its ability to carry out antigen presentation and rendering infected cells less sensitive to lysis by cytotoxic T lymphocytes . ORF8 suppresses type I interferon antiviral responses and interacts with host factors involved in pulmonary inflammation and fibrogenesis Rashid et al., 2021). From all viral proteomes interacting with human metalloproteome, the ORF8 proteins interact with 10 out of 58 human metalloproteins (Chasapis et al., 2021). Both SARS-CoV-2 and SARS-CoV ORF8 proteins play crucial roles in virus pathophysiological events, and dysregulate the TGF-β pathway, which is involved in the tissue fibrosis (Pereira, 2020). The functional implications of SARS-CoV-2 ORF8 had already gained immense attention and ORF8 is considered an important component of the immune evasion machinery (Li et al., 2020;Pereira, 2020;Mohammad et al., 2020;Alkhansa, Lakkis & El Zein, 2021). The SARS-CoV-2 ORF8 protein has less than twenty percent amino acid sequence homology with the SARS-CoV ORF8 protein, and represents a rapidly evolving viral protein (Flower et al., 2021;Velazquez-Salinas et al., 2020). A molecular framework for understanding the rapid evolution of ORF8, its contributions to COVID-19 pathogenesis, and the potential for its neutralization by antibodies have been supported by the structural analysis of the ORF8 protein (Hachim et al., 2020;Wang et al., 2020a). The crosstalk between SARS-CoV-2 or SARS-CoV infection and the host cell proteome at different levels may enable the identification of distinct and common molecular mechanisms . Of note, SARS-CoV-2 ORF8 interacts with a significant number of host proteins related to the endoplasmic reticulum quality control, glycosylation, and extracellular matrix organization, although the mechanism of action of ORF8 concerning those interacting proteins is uncertain (Wang et al., 2020a;Wu et al., 2021).
Functional implications on the immune surveillance due to the ORF8 truncation at position 27 remain unclear (Pereira, 2020). Therefore, it is of utmost importance to gain insight into the functionality of the truncated ORF8 protein variants to comprehend the B.1.1.7 lineage through theoretical and experimental characterization and genomic surveillance worldwide (Davies et al., 2021). The present study aimed at characterizing the unique variations of truncated ORF8 proteins (T-ORF8) due to the Q27STOP mutation. Further, this investigation differentiates a single T-ORF8 variant among 47 distinct unique T-ORF8 variants present in SARS-CoV-2 worldwide, as of May 20 th , 2021. Several clusters of the unique T-ORF8 have been identified based on the various bioinformatics features and phylogenetic relationships, along with the emerging variants of the unique T-ORF8.

DATA ACQUISITION AND METHODS
A total of 49,055 truncated ORF8 protein (T-ORF8) sequences (complete) from five continents (Asia, Africa, Europe, South America, and North America) were downloaded in FASTA format from the National Center for Biotechnology Information (NCBI) database (http://www.ncbi.nlm.nih.gov/). Note that no T-ORF8 protein sequence was found from Oceania. Next, FASTA files were processed in MATLAB 2021a for extracting unique T-ORF8 protein sequences for each continent. Note that only 47 unique T-ORF8 protein sequences were found. Here "unique T-ORF8" refers to a T-ORF8 protein sequence, which is different from other T-ORF8 sequences by the arrangement of amino acids, showing a non-zero Hamming distance from other T-ORF8 sequences. Consequently, the amino acid sequence of a "unique T-ORF8" variant is non-identical to other T-ORF8 sequences.

Derivation of polar/non-polar sequences and associated phylogeny
Every amino acid in a given T-ORF8 sequence was identified as polar (Q) or non-polar (P). Thus, every unique T-ORF8 became a binary sequence with two symbols P and Q. Then, the homology of these sequences was determined using the Clustal Omega web-suite (https://www.ebi.ac.uk/Tools/msa/clustalo/) and then associated with the nearest neighbor phylogenetic relationship among the unique T-ORF8 variants. Further, unique T-ORF8 variants with distinct binary polar/non-polar sequences were extracted (Hassan et al., 2020a;Broome & Hecht, 2000).

Frequency distribution of amino acids and phylogeny
The frequency of each amino acid present in a T-ORF8 sequence was determined using standard bioinformatics routine in Matlab-2021a. For each T-ORF8 protein, a twenty-dimensional frequency-vector considering the frequency of standard twenty amino acids can be obtained. Based on this frequency distribution of amino acids several consequences were drawn. The distance (Euclidean metric) between any two pairs of frequency vectors was calculated for each pair of T-ORF8 sequences. The distance matrix was used to develop a phylogenetic relationship based on the nearest neighbor-joining method using the standard routine in Matlab-2021a (Hassan et al., 2020c;Hassan, Choudhury & Roy, 2021).

Deep phylogenetic analyses
All phylogenetic data preparation and calculations were conducted in MEGA X (Kumar et al., 2018;Stecher, Tamura & Kumar, 2020). For deep phylogeny analyses we used two nucleotide datasets: one composed by the alignment of all 47 truncated ORF 8 sequences in addition to the RATG13 ORF8 as an external group, and a second group using all 47 truncated ORF 8, the RATG13 ORF 8 as well as 66 representative ORF 8 sequences for different Alpha, Beta, Gamma, Delta, Mu, GH/490R and Omicron variants. The phylogeny estimations were inferred by Maximum Likelihood using the Hasegawa-Kishino-Yano model (Hasegawa, Kishino & Yano, 1985). A discrete Gamma distribution was used compute the evolutionary rate differences among sites: four categories +G, parameter = 200.0000 and 500 bootstrap replications (Benvenuto et al., 2020). Furthermore, initial trees were heuristically obtained using Neighbor-Join and BioNJ algorithms with a Maximum Composite Likelihood (MCL) approach.

Amino acid conservation in terms of Shannon's entropy
The degree of conservation of amino acids embedded in a T-ORF8 protein was obtained by the well-known information-theoretic measure called "Shannon's entropy (SE)". For each T-ORF8 protein, Shannon's entropy of amino acid conservation over the amino acid sequence of T-ORF8 protein was calculated using as described in (Hassan et al., 2020c(Hassan et al., , 2021b. For a given T-ORF8 sequence of length l (here l = 26), the conservation of amino acids was calculated as follows: where p s i ¼ k i l ; k i represents the number of occurrences of an amino acid s i in the T-ORF8 sequence (Strait & Dewey, 1996).

Intrinsic disorder analysis
All 47 T-ORF8 variants were subjected to the per-residue disorder analysis, for which PONDR Ò VSL2 algorithm was employed (Obradovic et al., 2005). This tool showed good performance on proteins containing both structure and disorder and was favorably ranked in a recent Critical Assessment of protein Intrinsic Disorder prediction (CAID) experiment (Necci, Piovesan & Tosatto, 2021).

Finding functional motifs
The Eukaryotic Linear Motif (ELM) resource (http://elm.eu.org/) was used for finding functional sites in proteins (Kumar et al., 2020). ELMs (also known as short linear motifs (SLiMs)), are short protein interaction sites, which are commonly found in intrinsically disordered regions of proteins and define a wide range of protein functionality.

RESULTS
All 49,055 unique T-ORF8 protein variants were segregated from a set of available truncated ORF8 protein sequences collected from the NCBI database. Further, variability and commonality of the unique T-ORF8 proteins were analyzed from various quantitative measures as discussed in the methods section.

Characteristics of the unique variants of T-ORF8
The number of total sequences for each continent, the unique truncated ORF8 (T-ORF8) sequences, and their percentages are presented in Table 1. The results showed that 47 unique T-ORF8 proteins among the total of 48,691 were present in North America (Table 1). The unique T-ORF8 variants from Africa, Asia, Europe, and South America were contained in the set of unique T-ORF8 variants available in North America. Additionally, there were seven T-ORF8 with amino acid lengths 22, 24, 40 and 41 available in North America as of May 18, 2021 ( Table 2). Note that among the seven T-ORF8 sequences, only five were found to be unique, as mentioned in Table 2. As of May 18, 2021 a single copy of the T-ORF8 proteins of amino acid lengths of 24 and 41 (Table 2) were found. There were two T-ORF8 variants of 41 amino acids available in North America. The most frequent T-ORF8 proteins so far observed, were the T-ORF8 proteins of 26 amino acids. It was observed that the T-ORF8 arose due to truncation at the residue positions 23, 25, 27, 41, and 42 of the 121 amino acid full-length ORF8 protein.
We investigated the possible mutations for such truncations. A snapshot of the amino acid residues and their possible mutations with respect to the reference sequence NC 045512 is presented in Fig. S1. Table 1 Frequency and percentages unique T-ORF8 variants (continent-wise).

Continent
Total T-ORF8 (T) Unique Here 'U' stands for the total number of unique T-ORF8 variants over the total available T-ORF8 sequences, which is denoted by 'T'. Note that at four positions, 23, 25, 27, and 40, amino acids glutamine (Gln) and cysteine (Cys) were truncated due to mutations at the codon's first and third positions, respectively. The amino acid valine (Val) was truncated due to three mutations at the third, second, and first positions of the codon 'GUG'. Furthermore, it was observed that the mutations at the positions 23 and 25 were identical (C to U), and the changes of bases were transition mutations; i.e., pyrimidine (purine) to pyrimidine (purine). In contrast, the changes of bases of the truncated mutations at the positions 25 and 41 were transversal mutations; i.e., pyrimidine (purine) to purine (pyrimidine). For position 42, three sequences of mutations were hypothesized, taking place at first, second, and third positions of the codon (GUG); i.e., transition mutations (purine to purine), transversal mutation (pyrimidine to purine), and transversal mutation (purine to pyrimidine), respectively.
The list of unique T-ORF8 sequences of 26 amino acids with their representative accession IDs and sequences is presented in Table S1. Further, it was found that the unique T-ORF8 variants from Africa, Asia, Europe and South America were identical in relation to P15, as illustrated in Table S1. The date of sample collection, geo-location and accession ID of the first identified SARS-CoV-2 containing unique T-ORF8 variants are presented in Table S2.
Based on Table S2, the ORF8 protein sequence P15 was found in 48395 copies of the B.1.17 SARS-CoV-2 lineage in North America. Besides, the P15 variant with the Q27STOP mutation in the B.1.1.7 lineage was found in Africa, Asia, Europe and South America with a frequency of 108, 99, 156, and 1, respectively. None of the other 46 T-ORF8 unique variants was found on any continent, as of May 18, 2021. So, 46 unique T-ORF8 sequences were exclusively found in North America. Therefore, the P15 TORF8 variant is of particular interest for its uniqueness due to its apparent prevalence in most of the B.1.17 lineages of SARS-CoV-2 from North America and other continents.
In Europe, the P15 variant was first detected in two infected patients from Poland on March 15, 2020. In North America, two patients from Maryland were infected with the same SARS-CoV-2 P15 variant on May 27, 2020. After five days of the second occurrence of P15 in North America, one patient from Punjab-Pakistan (Asia) was infected by the P15 SARS-CoV-2 variant. Six months thereafter, the same variant was found in a patient from Ghana, for the first time in Africa. Twenty days after the fifth occurrence in Africa, the P15 variant was identified in Peru (South America) on December 31, 2020 Additionally, the frequency distribution of the T-ORF8 P15 variants across the North American continent is presented in Table 3. It was found that the T-ORF8 P15 variant spread over three geo-locations, Michigan, Florida, and Minnesota, with the highest number of frequencies of 5084, 6884, and 7416, respectively. The P15 variant was found for the first time in Maryland, but the frequency at this geo-location was 1171 on May 14, 2021.
There were 18 geo-locations, where the frequency of spread of the P15 variant was found to be less than 100 (Table 3). Among other geo-locations, Guam (US territory located in the Pacific Ocean) and North Dakota, USA, had the least number of patients infected by the B.1.1.7 variant containing the P15 protein. In Guam, according to the NCBI SARS-CoV-2 database, all seven patients were infected by the B.1.1.7 variant containing the P15, within a short period from February 21 to April 11, 2021. Also, in North Dakota, 13 of 16 patients were infected by the same strain of SARS-CoV-2 from February 2, 2021 to April 28, 2021.
The frequency distribution of all T-ORF8 variants across the US is presented in Table 4. It is evident that all 47 unique T-ORF8 variants were detected in 21 different states of the  US. The highest number (7) of the unique T-ORF8 variants was detected as a first instance in Pennsylvania within a short period (March 2 to April 20, 2021) ( Table 4). The P35 variant was found initially in two states: Rhode Island and Massachusetts on March 20, 2021. Furthermore, it was observed that all T-ORF8 variants other than P15 emerged for the first time from February 12, 2021 to April 28, 2021.
Using the Clustal Omega web-server, an amino acid sequence-based alignment and corresponding phylogenetic tree of the unique T-ORF8 variants are presented in Fig. S2. From the sequence alignment, it was derived that all unique T-ORF8 variants share identical amino acids methionine (Met), lysine (Lys), Gln, serine (Ser), and leucine (Leu) at positions 1, 2, 18, 21, and 22 respectively. Further it was found that T-ORF8 P15 is closest to the ORF8 sequences P13 and P14 (Fig. S2). Note that P15 was placed at the leftmost branch of the phylogenetic tree, which made the sequence P15 distinguishable Next, we conducted deep phylogenic analysis. The first nucleotide dataset used for this analysis included the alignment of all 47 truncated ORF8 sequences in addition to the RATG13 ORF8 as an external group. Phylogenic analysis of this group returned a tree ( Fig. 1) with the highest log likelihood of −400.62 in an analysis with 48 nucleotide sequences and a total of 83 positions in the final dataset. In addition, Fig. 1 shows nine well-defined monophyletic groups, where the ORF 8 sequences 15 and 40 formed a unique clade in the group II. Based on this tree analysis it can be inferred that at least nine truncated ORF8 variants could be related to a specific SARS-CoV-2 variant and/or a specific variant subtype, in this case more related to de Alpha type. Interestingly, sequences 35 and 46 rooted outside the tree together with the external group ORF8 from the RATG13 genome. In these cases, the sequences 35 and 46 are possibly mutating to the corresponding SARS-CoV-2 start point or they could be related to a subtype with a small viral load and spread.
In the second dataset there were all 47 truncated ORF8 variants, the RATG13 ORF8, as well as 66 representative ORF8 sequences from different Alpha, Beta, Gamma, Delta, Mu, GH/490R, and Omicron variants. Results of the phylogenetic analysis of this set containing all 47 sequences and different SARS-CoV-2 ORF8 variant representatives are shown in Fig. S3, where the resultant tree presented a highest log likelihood of −430.29.
This analysis involved 114 nucleotide sequences with a total of 81 positions in the final dataset. In this tree, one can find at least 14 group clades, and, as expected, almost all ORF8 variants are grouped together in the group I. The other 47 truncated ORF8 sequences presented similar tree topologies in comparison to the first dataset tree (cf. Figs. 1 and S3

Evaluation of intrinsic disorder content of 47 T-ORF8 proteins
Unfortunately, no structural information is available for the truncated forms of ORF8. In fact, although two X-ray structures were reported for the dimeric form of the SARS-CoV-2 ORF8 protein, both of these structures were solved for the ORF8 sequences containing residues 18-121; i.e., they do not include information for more than a half (63%) of the N-terminal region of the full-length ORF8, which constitutes T-ORF8. Furthermore, truncated forms of ORF8 are relatively short to have independently foldable structure. It would be really important to conduct some structural analysis of the truncated ORF8 (e.g., by solution NMR). However, such an analysis could be complicated by the presence of two cysteine residues and by the highly hydrophobic nature of this region showing the mean hydrophobicity of 0.5926, which dramatically exceeds the mean hydrophobicity of typical globular proteins (~0.46 ± 0.05). Therefore, to gain some structure-related information for the truncated forms of ORF8, we analyzed the peculiarities of the distribution of per-residue intrinsic disorder predisposition within sequences of the 47 T-ORF8 variants. Since the amino acid sequences of T-ORF8 proteins are shorter than 30 residues, the number of computational tools capable of predicting the intrinsic disorder is limited. In this study, we used the PONDR Ò VSL2 algorithm. The results of this analysis are shown in Fig. 2. Due to their short length and limited sequence variability, T-ORF8 proteins are characterized by rather featureless disorder profiles, where both N-and C-terminal regions are predicted to have higher levels of intrinsic disorder than the central parts. Most T-ORF8 proteins show rather similar profiles, with the noticeable exceptions of P1 and P36, which show the highest disorder levels in their N-terminal regions. In contrast, P45 presents the least disorder at the N-terminus, P25 the longest and most peculiar disorder distribution in its C-terminal half, P18 and P19 long disorder stretches at their C-termini, and P12 the lowest levels of disorder in the C-terminal region (Fig. 2A). These observations are further supported by Fig. 2B, where the 47 T-ORF8 proteins are ranked based on their mean disorder scores, from the highest to the lowest levels of disorder. However, the vast majority of T-ORF8 proteins (38 of 47) form a rather uniform cluster with the average mean disorder score of 0.304 ± 0.010, whereas P25, P19, P36, P18, and P1 show higher than average and P13, P40, P23, and P12 lower than average levels of disorder. Table S3 lists potential functional motifs identified in the 47 T-ORF8 variants by ELM resource and shows that all T-ORF8 proteins have several such motifs. Based on their content of functional motifs, T-ORF8 proteins can be grouped into 21 clusters, with three clusters containing 13, 4, and 2 proteins, respectively, and all the remaining being singletons. The common motif found in all T-ORF8 proteins is the N-degron that initiates protein degradation by binding to the UBR-box of N-recognins. A kinase docking motif that mediates interaction towards the ERK1/2 and P38 subfamilies of MAP kinases and a Ser/Thr (serine/threonine) residue phosphorylated by the Plk1 kinase are present in 20 clusters, whereas 17 clusters also include a site for attachment of a fucose residue to a serine. The lowest number of functional motifs (3) is found in 6 proteins (P12, P16, P17, P19, P21, and P40), many of which are characterized by lower mean disorder scores. On the contrary, proteins with the largest number of functional motifs (6 and 7) typically show higher disorder scores. Table S3 shows that truncation might generate functional T-ORF8 variants (or at least variants possessing functional motifs), and that expected functionality of different T-ORF8 proteins can be quite different. It is clear that the results of this computational analysis should be taken with caution, and the functionality of T-ORF8 requires experimental validation.

Variability and commonality of T-ORF8 variants
In the proceeding section, the quantification of unique T-ORF8 variants using various parameters such as polar/non-polar residue sequence homology, amino acid frequency distributions, amino acid conservation through the Shannon entropy, and physicochemical properties is described.
Note that, the P15 variant was placed in a single leaf and found to be distant from the other unique ORF8 variants as per polarity-based homology, although P15 was closest to the T-ORF8 variants P13 and P14 based on amino acid homology. Furthermore, it was noticed that only 17 unique T-ORF8 variants possessed unique polar/non-polar sequences (Table S4). The polar/non-polar sequence of each T-ORF8 variant other than P4, P5, P15, and P28 was unique.
Surprisingly, among the total of 47 T-ORF8 variants, there were 28 T-ORF8 variants, which share identical polar/non-polar sequence with that of P15. According to the phylogenetic relationship derived from the unique polar/non-polar sequence homology, the T-ORF8 P15 was found to be closest to P42. Furthermore, the pairs (P13, P25), (P21, P40), and (P5, P30) were found to be close enough to each other (see Fig. S5).

Variability of the frequency distribution of amino acids present in T-ORF8 variants
The frequency of each amino acid present in the unique T-ORF8 variants was enumerated, and consequently, a twenty-dimensional frequency vector was obtained (Table S5). Tryptophan (Trp) was not present in any of the unique T-ORF8 variants. It was noted that the amino acids arginine (Arg), asparagine (Asn), aspartic acid (Asp), proline (Pro), and tyrosine (Tyr) were absent in the T-ORF8 P15. Arg was found with frequency one in the T-ORF8 P17, P39, P19, P22, and P33. In the P14 and P41 sequences, Asn was present with frequency one. Likewise, Asp was found in P38 and P11. Pro with frequency one, was found in the P8 variant only. Tyr was found in the T-ORF8 P20 and P23 variants. The highest frequency of 4 was seen for phenylalanine (Phe) in P3, P16, and P47, Leu in P10, P12, P24, P34, and P35, and threonine (Thr) in P29, P31, P32, and P42.
For each pair of frequency vectors corresponding to all unique T-ORF8 variants, Euclidean distances were calculated (Table S6), and the distance matrix in color heat-map is presented in Fig. 3. It was found that the P15 variant is equidistant (1.41) from all other variants except P30 and P40, which are one distance apart from P15. Further, we observed that the distance between any two pairs of T-ORF8 variants is two (light green color) except in a few cases (Fig. S6). Although the amino acid sequences were different, identical frequency vectors were found for the pair of ORF8 variants ( Based on the distance matrix, all unique T-ORF8 variants were clustered, and the associated phylogeny is presented in Fig. S6. The P15 variant was very close to P22, P23, P33, P40, and P41 according to the phylogenetic relationship depicted in Fig. S6. Other than the pairs of T-ORF8 having identical frequency vectors, it was found that the pairs of the unique T-ORF8 variants (P23, P33), (P14, P30), (P19, P20), and (P31, P32) were close to each other as derived from the phylogenetic relationship (Fig. S6).

Variability of T-ORF8 through Shannon entropy
Shannon entropy (SE) for each unique T-ORF8 variant was calculated using the formula stated in "Deep Phylogenetic Analyses" (Table S7). It was found that the highest and lowest SEs of the 47 unique T-ORF8 proteins were 0.958 and 0.973, respectively. That is, the length of the largest interval is 0.015, which is sufficiently small. Based on SEs of the T-ORF8 proteins a set of clusters were derived (Fig. S7A) SEs of each of the T-ORF8 variants are plotted in Fig. S7B. The largest cluster containing 18 T-ORF8 variants (including the T-ORF8 P15) based on the identical SEs were obtained (Fig. S7).

Molecular and physicochemical informatics of unique T-ORF8 variants
For each unique T-ORF8 variant and complete ORF8 protein, several physicochemical and molecular properties were computed using the web-servers. It was found that the extinction coefficient of all T-ORF8 variants was 125, except for four T-ORF8 variants, P16, P17, P18, and P19, whose extinction coefficient was zero (see Table S8). Further, it was noticed that for P20 and P23, extinction coefficients were found to be significantly higher compared to the others. Instability indices of all the T-ORF8 protein variants were ranging from 45.36 to 95.85 (greater than 40), and consequently they are all unstable. It was observed that the P15 variant had a unique frequency of the various types of residues (Tiny: 10, Small: 12, Aliphatic: 9, Aromatic: 4, Non-polar: 16, Polar: 10, Charged: 3, Basic: 2, Acidic: 1) and none of the other T-ORF8 variants was identical.
Furthermore, Euclidean distances between every pair of molecular and physicochemical property vectors corresponding to each T-ORF8 variant were computed and a phylogenetic relationship was derived (Fig. 4) based on the distance matrix (Table S9). Note that the property vectors of P20 and P30 were highly distant from the other ORF8 variants due to the huge difference in extinction coefficients (for P20, EC: 1490 and for P30, EC: 1615). So, ignoring these two ORF8 variants, the phylogenetic relationship among the remaining 45 T-ORF8 was derived. It was found that none of the T-ORF8 variants had identical property vectors to the P15 variant. It was further found from the phylogenetic relationship (Fig. 4B) Table S10.
In the close vicinity of P15, only the P25, P30, and P36 variants appeared based on the nearness of property vectors (Table S10).

Possible T-ORF8 variants in the likelihood of P15 variant
Based on the amino acid sequence homology and other various features, such as the frequency distribution of amino acids, SE, and physicochemical properties of T-ORF8 variants, a possible cluster of nine unique T-ORF8 variants are derived. A schematic presentation is given in Fig. 5. All these nine unique T-ORF8 variants had unique polar/non-polar sequences as shown in Table S4. In addition to the P15 variant, these possible nine emerging variants are likely to appear in the B.1.1.7 lineage of SARS-CoV-2 in the near future. As of May 22 nd , 2021, it was observed that 16 of 17 COVID-19 affected patients from India (mostly from Gujrat), were infected by the B.1.1.7 lineage of SARS-CoV-2 with the P15 variant, and only one patient (Accession: QVO43928) infected on February 28, 2021 with the SARS-CoV-2 strain with the P34 T-ORF8 variant, which had an identical polar/non-polar sequence as that of P15.

DISCUSSION AND CONCLUDING REMARKS
The ORF8 protein is 121 amino acid long with two genotypes (orf8L and orf8S). It has an Ig-like fold, is highly immunogenic, and interacts with 47 human proteins, 15 of them being drug targets interacting with MHC-I molecules leading to a significant down-regulation of their surface expression on various cell types (Rashid et al., 2021;Gordon et al., 2020;Gamage et al., 2020). As a result, inhibition of ORF8 could boost special immune surveillance and speed up SARS-CoV-2 eradication in vivo (Gamage et al., 2020). ORF8 is not like ORF3a, an ion channel (viroporin), implicated in virion assembly and membrane budding both in SARS-CoV and SARS-CoV-2. In contrast to SARS-CoV, which is not viable when lacking E and ORF3a proteins, and which requires the full-length E and ORF3a proteins for maximal replication and virulence (Barrantes, 2021;Castaño-Rodriguez et al., 2018;Tan et al., 2021), ORF8 in SASR-CoV-2 seems to only have a minor or no impact on the viral life cycle, as the virus can seemingly survive without a functional ORF8 protein, which has been demonstrated by the presence of many mutations and truncations detected in viable SARS-CoV-2 variants (Wang et al., 2020a. The Q27STOP mutation in the ORF8 protein has been discovered to cause 47  An important consequence of the ORF8 truncation is the alterations in the presentation of this protein by the human leukocyte antigen (HLA) complex on the surface of T-cells, which are among the key players in the immune response to viral infection. In fact, the development of the T-cell-based immunity is based on the presentation of short viral peptides on the cell surface by the HLA complex. Activation of killer CD8 T-cells depends on the recognition of viral peptides presented by HLA class I molecules, whereas activation of CD4 T lymphocytes (helper T-cells) is initiated by binding to a complex between viral peptides and HLA class II molecules (Klein & Sato, 2000). Although the  & Sato, 2000;Swain, McKinstry & Strutt, 2012). The overall importance of the T-cell-based responses in COVID-19 severity and long-term immunity has been documented in multiple reports (Wang et al., 2020b;Shkurnikov et al., 2021;Iturrieta-Zuazo et al., 2020;Bange et al., 2021;Grifoni et al., 2020;Peng et al., 2020;Dan et al., 2021). Therefore, it is not surprising that constant appearance of novel mutations in the SARS-CoV-2 genome can target T-cell epitopes (Agerer et al., 2021;Reynolds et al., 2021). Potential CD8 and CD4 epitopes represent peptides derived from the viral proteins, where 8-to 14-mers and 15-to 20-mers are serving as partners for HLA class I and class II receptors, respectively. The appearance of the premature stop codon in the ORF8 gene encoding the NS8 (ORF8) protein (Q27stop) not only generates the truncated form of this protein due to the deletion of almost 80% of the ORF8 protein, but also eliminates the whole immunopeptidome associated with this part of protein. Therefore, it is likely that such distortion in the immunopeptidome of ORF8 will dramatically affect its immunogenicity. Furthermore, mutations found in T-ORF8 could further modulate T-cell immunity.
Quantitative characteristics of the 47 unique truncated ORF8 protein variants were examined. All 47 T-ORF8 variants were found in North America, and only the P15 T-ORF8 variant was spread to four other continents: Africa, Asia, Europe and South America, until May 22, 2021. In this regard, it is pertinent to raise the question of whether there is any correlation between the spreading of all unique T-ORF8 variants and the epidemiological nature of North America. Within North America, it was reported that one of the top mutations, 27964C>T-(S24L) in the ORF8 protein, has an unusually strong gender dependence . The spread of the P15 variants over the 57 geo-locations across North America was noticed, and in addition, many patients from Asia, Africa, South America and Europe were infected by the particular B.1.1.7 variant of SARS-CoV-2, which contains the P15 variant. Like in many states of the US, also in the US territory of Guam and in North Dakota, most of the patients were noticed to have contracted the P15 variant of the B.1.1.7 lineage. Consequently, the present trend implies that a much higher spread of this lineage with this particular P15 variant is likely to occur. After Europe, the first case of the B.1.1.7 variant with the T-ORF8 P15 was discovered in Maryland in the US, but although later this strain remained limited in Maryland it spread further to other states, such as Florida and Minnesota (Table 3). Furthermore, this analysis reports a set of nine most likely T-ORF8 variants P4, P5, P13, P21, P25, P30, P36, P40, and P42, which were found to be residing in close vicinity of the P15 ORF8 variant. It was noticed that among 47 unique T-ORF8 variants, 28 of them had identical polar/non-polar sequences to that of the P15 variant. Considering the ability of the P15 variant to spread one can assume that the 28 variants with identical polar/non-polar sequences may spread in the near future and cause third, fourth, and fifth waves of COVID-19. As evidence, one patient from India was infected with SARS-CoV-2 with the P34 variant, which has the same polar/non-polar sequences as the P15 variant, as of May 22, 2021 (NCBI accession: QVO43928). The fact that T-ORF8 is still operating as ORF8, is an open issue that needs to be addressed. Reports try to link these T-ORF8 present in many lineages to COVID-19 severity and/or outcomes, effects that contribute to disease progression if associated with mutations in spike protein (Pereira, 2020;Guthmiller et al., 2021;Nagy, Pongor & Győrffy, 2021). It has also been reported that patients infected with SARS-CoV-2, lacking the majority of ORF8 protein, have a lower risk of aggravation, a conclusion that accrued variants in the spike, ORF8, and ORF3a proteins were associated with improved clinical outcomes (Esper et al., 2021;Young et al., 2020). More recently, SARS-CoV-2 strains were isolated in Washington state (USA), with a stop codon mutation generating a novel truncated and much shorter ORF8 protein, as well as in Hong Kong, which completely lacked ORF8 (gene, protein and antibody), ORF7a, and ORF7b (Esper et al., 2021;DeRonde et al., 2021;Tse et al., 2021). However, the in vitro analysis on Nasal Epithelial cells (NECs) infected with one of these isolates (ORF8-Δ382) showed no significant functional differences between the wild type ORF8 and the ORF-Δ382 mutant (Gamage et al., 2020). In contrast, Vero-6 cell infected with the same strain (ORF8-Δ382) showed significantly higher replicative fitness in vitro than the wild type, while no difference was observed in the patient viral load, indicating that the deletion variant retained its replicative fitness . In any case, the combinatorial clinical effects of T-ORF8 need to be investigated and analyzed in depth. It is necessary to investigate in detail the functions of T-ORF8 and the effects of this protein on inflammation and antigen-presenting ability. Finally, caution should be paid to using ORF8 as a diagnostic marker, as many immunoassay tests depend on antibody potency (Pereira, 2021). A systematic analysis of this protein and its specific antibodies is needed to determine the effects of these mutations/truncations on the diagnostic potential of the anti-ORF8 antibodies.

ADDITIONAL INFORMATION AND DECLARATIONS Funding
The authors received no funding for this work.

Competing Interests
Vasco Azevedo, Debmalya Barh and Vladimir N Uversky are Academic Editors for PeerJ.
Kenneth Lundstrom is employed by PanTherapeutics.

Author Contributions
Sk. Sarif Hassan conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.
Vaishnavi Kodakandla performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Elrashdy M. Redwan performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft.
Kenneth Lundstrom conceived and designed the experiments, performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Pabitra Pal Choudhury performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft.
Tarek Mohamed Abd El-Aziz performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Kazuo Takayama performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Ramesh Kandimalla performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Amos Lal performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Ángel Serrano-Aroca performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Gajendra Kumar Azad performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Alaa AA. Aljabali performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Giorgio Palù performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Gaurav Chauhan performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Parise Adadi performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Murtaza Tambuwala performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Adam M. Brufsky performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Wagner Baetas-da-Cruz performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Debmalya Barh performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Vasco Azevedo performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Nikolas G. Bazan performed the experiments, analyzed the data, authored or reviewed drafts of the paper, and approved the final draft. Bruno Silva Andrade conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft. Raner José Santana Silva performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.
Vladimir N. Uversky conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, and approved the final draft.

Data Availability
The following information was supplied regarding data availability: The data are available in the article and the Supplemental File.

Supplemental Information
Supplemental information for this article can be found online at http://dx.doi.org/10.7717/ peerj.13136#supplemental-information.